Publications

Lorena Poenaru-Olaru, June Sallou, Luís Cruz, Jan S. Rellermeyer, Arie van Deursen (2023). Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques. GREENS. Preprint.

Tim Yarally, Luís Cruz, Daniel Feitosa, June Sallou, Arie van Deursen (2023). Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI. CAIN23, 2nd International Conference on AI Engineering - Software Engineering for AI. 🏆 ACM SIGSOFT Distinguished Paper Award. Preprint. Arxiv.

Roberto Verdecchia, June Sallou, Luís Cruz (2022). A Systematic Review of Green AI. Submitted to WIREs Data Mining and Knowledge Discovery. Preprint.

Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer (2022). Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study. 7th Workshop on Real-time Stream Analytics, Stream Mining, CER/CEP & Stream Data Management in Big Data. Preprint. Arxiv.

Ching-Chi Chuang, Luis Cruz, Robbert van Dalen, Vladimir Mikovsk and Arie van Deursen (2022). Removing dependencies from large software projects: are you really sure?. SCAM – 22nd IEEE International Working Conference on Source Code Analysis and Manipulation. Preprint.

Roberto Verdecchia, Luís Cruz, June Sallou, Michelle Lin, James Wickenden, Estelle Hotellier (2022). Data-Centric Green AI An Exploratory Empirical Study. 2022 International Conference on ICT for Sustainability (ICT4S). Preprint. Arxiv.

Arumoy Shome, Luís Cruz, and Arie van Deursen (2022). Data Smells in Public Datasets. CAIN’22 - 1st International Conference on AI Engineering – Software Engineering for AI. Arxiv.

Haiyin Zhang, Luís Cruz, and Arie van Deursen (2022). Code Smells for Machine Learning Applications. CAIN’22 - 1st International Conference on AI Engineering – Software Engineering for AI. Arxiv.

Jai Kannan, Scott Barnett, Luís Cruz, Anj Simmons, Akash Agarwal (2022). MLSmellHound: A Context-Aware Code Analysis Tool. ICSE’22 - NIER. Arxiv.

Bart van Oort, Luís Cruz, Babak Loni, Arie van Deursen (2022). “Project smells” – Experiences in Analysing the Software Quality of ML Projects with mllint. International Conference on Software Engineering (ICSE 2022), SEIP track. Arxiv.

Daniel Feitosa, Luís Cruz, Rui Abreu, João Paulo Fernandes, Marco Couto, João Saraiva (2021). Patterns and Energy Consumption: Design, Implementation, Studies, and Stories. Book Chapter in Software Sustainability. Preprint.

Mark Haakman, Luís Cruz, Hennie Huijgens, Arie van Deursen (2021). AI Lifecycle Models Need to be Revised. An Exploratory Study in Fintech. Empirical Software Engineering. Preprint.

Sofia Reis, Rui Abreu, Luís Cruz (2021). Fixing Vulnerabilities Potentially Hinders Maintainability. Empirical Software Engineering. Preprint. Arxiv.

Yuanhao Xie, Luís Cruz, Petra Heck, Jan Rellermeyer (2021). Systematic Mapping Study on the Machine Learning Lifecycle. WAIN’21 - 1st Workshop on AI Engineering – Software Engineering for AI. Arxiv.

Petra Heck, G Schouten, Luís Cruz (2021). A Software Engineering Perspective on Building Production-Ready Machine Learning Systems. Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry (pp. 23-54).

Bart van Oort, Luís Cruz, Maurício Aniche, Arie van Deursen (2021). The Prevalence of Code Smells in Machine Learning projects. WAIN’21 - 1st Workshop on AI Engineering – Software Engineering for AI. Preprint.

Luís Cruz and Rui Abreu (2019). Improving Energy Efficiency Through Automatic Refactoring. Journal of Software Engineering and Research Development (JSERD).

Luis Cruz and Rui Abreu (2019). On the Energy Footprint of Mobile Testing Frameworks. IEEE Transactions on Software Engineering. Preprint. Slides.

Luís Cruz and Rui Abreu and John Grundy and Li Li and Xin Xia (2019). Do Energy-oriented Changes Hinder Maintainability?. ICSME. Preprint. Slides.

Luís Cruz, Rui Abreu (2019). EMaaS: Energy Measurements as a Service for Mobile Applications. 41st International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER). Preprint.

Luís Cruz, Rui Abreu and David Lo (2019). To the Attention of Mobile Software Developers: Guess What, Test your App!. In Empirical Software Engineering.
Slides.

Luís Cruz and Rui Abreu (2019). Catalog of Energy Patterns for Mobile Applications. Empirical Software Engineering. 🏆 Best Presentation Award BENEVOL 2019. Preprint.

Luís Cruz and Rui Abreu (2018). Using Automatic Refactoring to Improve Energy Efficiency of Android Apps. CIbSE XXI Ibero-American Conference on Software Engineering. 🏆 Best Paper Award. Preprint. Arxiv.

Luís Cruz and Rui Abreu (2017). Performance-based Guidelines for Energy Efficient Mobile Applications. IEEE/ACM International Conference on Mobile Software Engineering and Systems, MobileSoft 2017. 🏆 Most Influential Paper Award 2023. Preprint. Slides.

Luis Cruz, Rui Abreu and Jean-Noel Rouvignac (2017). Leafactor: Improving Energy Efficiency of Android Apps via Automatic Refactoring. IEEE/ACM International Conference on Mobile Software Engineering and Systems, MobileSoft 2017.
Slides.

Luís Cruz, Jonathan Rubin, Rui Abreu, Shane Ahern, Hoda Eldardiry, Daniel G. Bobrow (2015). A wearable and mobile intervention delivery system for individuals with panic disorder. Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia (pp. 175–182). Preprint.

Pedro Strecht, Luís Cruz, Carlos Soares, João Mendes-Moreira and Rui Abreu (2015). A Comparative Study of Regression and Classification Algorithms for Modelling Students’ Academic Performance. Educational Data Mining 2015. Full-text.

Cruz, Luis and Reis, Luis Paulo and Lau, Nuno and Sousa, Armando (2012). Optimization approach for the development of humanoid robots’ behaviors. Advances in Artificial Intelligence–IBERAMIA 2012 (pp. 491–500). Springer Berlin Heidelberg. Preprint.

Luís Cruz, Luis Paulo Reis and Luis Rei (2011). Generic optimization of humanoid robots’ behaviours 15th Portuguese Conference on Artificial Intelligence, EPIA (pp. 385–397).